scholarly journals A Model Study of In Silico Proficiency Testing for Clinical Next-Generation Sequencing

2016 ◽  
Vol 140 (10) ◽  
pp. 1085-1091 ◽  
Author(s):  
Eric J. Duncavage ◽  
Haley J. Abel ◽  
Jason D. Merker ◽  
John B. Bodner ◽  
Qin Zhao ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Proficiency Testing ◽  
In Silico ◽  
Absolute Difference ◽  
Ion Torrent ◽  
Next Generation ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Clinical Laboratories ◽  
Generation Sequencing

Context.—Most current proficiency testing challenges for next-generation sequencing assays are methods-based proficiency testing surveys that use DNA from characterized reference samples to test both the wet-bench and bioinformatics/dry-bench aspects of the tests. Methods-based proficiency testing surveys are limited by the number and types of mutations that either are naturally present or can be introduced into a single DNA sample. Objective.—To address these limitations by exploring a model of in silico proficiency testing in which sequence data from a single well-characterized specimen are manipulated electronically. Design.—DNA from the College of American Pathologists reference genome was enriched using the Illumina TruSeq and Life Technologies AmpliSeq panels and sequenced on the MiSeq and Ion Torrent platforms, respectively. The resulting data were mutagenized in silico and 26 variants, including single-nucleotide variants, deletions, and dinucleotide substitutions, were added at variant allele fractions (VAFs) from 10% to 50%. Participating clinical laboratories downloaded these files and analyzed them using their clinical bioinformatics pipelines. Results.—Laboratories using the AmpliSeq/Ion Torrent and/or the TruSeq/MiSeq participated in the 2 surveys. On average, laboratories identified 24.6 of 26 variants (95%) overall and 21.4 of 22 variants (97%) with VAFs greater than 15%. No false-positive calls were reported. The most frequently missed variants were single-nucleotide variants with VAFs less than 15%. Across both challenges, reported VAF concordance was excellent, with less than 1% median absolute difference between the simulated VAF and mean reported VAF. Conclusions.—The results indicate that in silico proficiency testing is a feasible approach for methods-based proficiency testing, and demonstrate that the sensitivity and specificity of current next-generation sequencing bioinformatics across clinical laboratories are high.

scholarly journals Using Machine Learning to Identify True Somatic Variants from Next-Generation Sequencing

2019 ◽  
Vol 66 (1) ◽  
pp. 239-246 ◽  
Author(s):  
Chao Wu ◽  
Xiaonan Zhao ◽  
Mark Welsh ◽  
Kellianne Costello ◽  
Kajia Cao ◽  
...  
Keyword(s):  
Machine Learning ◽  
Next Generation Sequencing ◽  
Clinical Laboratory ◽  
Next Generation ◽  
Single Nucleotide Variants ◽  
Test Set ◽  
Clinical Laboratories ◽  
Bona Fide ◽  
Validation Set ◽  
Generation Sequencing

Abstract BACKGROUND Molecular profiling has become essential for tumor risk stratification and treatment selection. However, cancer genome complexity and technical artifacts make identification of real variants a challenge. Currently, clinical laboratories rely on manual screening, which is costly, subjective, and not scalable. We present a machine learning–based method to distinguish artifacts from bona fide single-nucleotide variants (SNVs) detected by next-generation sequencing from nonformalin-fixed paraffin-embedded tumor specimens. METHODS A cohort of 11278 SNVs identified through clinical sequencing of tumor specimens was collected and divided into training, validation, and test sets. Each SNV was manually inspected and labeled as either real or artifact as part of clinical laboratory workflow. A 3-class (real, artifact, and uncertain) model was developed on the training set, fine-tuned with the validation set, and then evaluated on the test set. Prediction intervals reflecting the certainty of the classifications were derived during the process to label “uncertain” variants. RESULTS The optimized classifier demonstrated 100% specificity and 97% sensitivity over 5587 SNVs of the test set. Overall, 1252 of 1341 true-positive variants were identified as real, 4143 of 4246 false-positive calls were deemed artifacts, whereas only 192 (3.4%) SNVs were labeled as “uncertain,” with zero misclassification between the true positives and artifacts in the test set. CONCLUSIONS We presented a computational classifier to identify variant artifacts detected from tumor sequencing. Overall, 96.6% of the SNVs received definitive labels and thus were exempt from manual review. This framework could improve quality and efficiency of the variant review process in clinical laboratories.

scholarly journals Prostate cancer heterogeneity assessment with multi-regional sampling and alignment-free methods

2020 ◽  
Vol 2 (3) ◽  
Author(s):  
Ross G Murphy ◽  
Aideen C Roddy ◽  
Shambhavi Srivastava ◽  
Esther Baena ◽  
David J Waugh ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Next Generation ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Cancer Heterogeneity ◽  
Alignment Free ◽  
Treatment Indications ◽  
Patient Heterogeneity ◽  
Genomic Locations ◽  
Generation Sequencing

Abstract Combining alignment-free methods for phylogenetic analysis with multi-regional sampling using next-generation sequencing can provide an assessment of intra-patient tumour heterogeneity. From multi-regional sampling divergent branching, we validated two different lesions within a patient’s prostate. Where multi-regional sampling has not been used, a single sample from one of these areas could misguide as to which drugs or therapies would best benefit this patient, due to the fact these tumours appear to be genetically different. This application has the power to render, in a fraction of the time used by other approaches, intra-patient heterogeneity and decipher aberrant biomarkers. Another alignment-free method for calling single-nucleotide variants from raw next-generation sequencing samples has determined possible variants and genomic locations that may be able to characterize the differences between the two main branching patterns. Alignment-free approaches have been applied to relevant clinical multi-regional samples and may be considered as a valuable option for comparing and determining heterogeneity to help deliver personalized medicine through more robust efforts in identifying targetable pathways and therapeutic strategies. Our study highlights the application these tools could have on patient-aligned treatment indications.

scholarly journals Proficiency Testing of Standardized Samples Shows Very High Interlaboratory Agreement for Clinical Next-Generation Sequencing–Based Oncology Assays

2018 ◽  
Vol 143 (4) ◽  
pp. 463-471 ◽  
Author(s):  
Jason D. Merker ◽  
Kelly Devereaux ◽  
A. John Iafrate ◽  
Suzanne Kamel-Reid ◽  
Annette S. Kim ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Proficiency Testing ◽  
False Negative ◽  
High Specificity ◽  
Variant Allele ◽  
Next Generation ◽  
Single Nucleotide Variants ◽  
Sequencing Platform ◽  
Negative Results ◽  
Generation Sequencing

Context.— Next-generation sequencing–based assays are being increasingly used in the clinical setting for the detection of somatic variants in solid tumors, but limited data are available regarding the interlaboratory performance of these assays. Objective.— To examine proficiency testing data from the initial College of American Pathologists (CAP) Next-Generation Sequencing Solid Tumor survey to report on laboratory performance. Design.— CAP proficiency testing results from 111 laboratories were analyzed for accuracy and associated assay performance characteristics. Results.— The overall accuracy observed for all variants was 98.3%. Rare false-negative results could not be attributed to sequencing platform, selection method, or other assay characteristics. The median and average of the variant allele fractions reported by the laboratories were within 10% of those orthogonally determined by digital polymerase chain reaction for each variant. The median coverage reported at the variant sites ranged from 1922 to 3297. Conclusions.— Laboratories demonstrated an overall accuracy of greater than 98% with high specificity when examining 10 clinically relevant somatic single-nucleotide variants with a variant allele fraction of 15% or greater. These initial data suggest excellent performance, but further ongoing studies are needed to evaluate the performance of lower variant allele fractions and additional variant types.

scholarly journals Proficiency Testing of Standardized Samples Shows High Interlaboratory Agreement for Clinical Next-Generation Sequencing–Based Hematologic Malignancy Assays With Survey Material–Specific Differences in Variant Frequencies

2020 ◽  
Vol 144 (8) ◽  
pp. 959-966 ◽  
Author(s):  
Alissa Keegan ◽  
Julia A. Bridge ◽  
Neal I. Lindeman ◽  
Thomas A. Long ◽  
Jason D. Merker ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Proficiency Testing ◽  
Hematologic Malignancy ◽  
False Negative ◽  
False Negative Rate ◽  
Hematologic Malignancies ◽  
Variant Allele ◽  
Next Generation ◽  
Single Nucleotide Variants ◽  
Generation Sequencing

Context.— As laboratories increasingly turn from single-analyte testing in hematologic malignancies to next-generation sequencing–based panel testing, there is a corresponding need for proficiency testing to ensure adequate performance of these next-generation sequencing assays for optimal patient care. Objective.— To report the performance of laboratories on proficiency testing from the first 4 College of American Pathologists Next-Generation Sequencing Hematologic Malignancy surveys. Design.— College of American Pathologists proficiency testing results for 36 different engineered variants and/or allele fractions as well as a sample with no pathogenic variants were analyzed for accuracy and associated assay performance characteristics. Results.— The overall sensitivity observed for all variants was 93.5% (2190 of 2341) with 99.8% specificity (22 800 of 22 840). The false-negative rate was 6.5% (151 of 2341), and the largest single cause of these errors was difficulty in identifying variants in the sequence of CEBPA that is rich in cytosines and guanines. False-positive results (0.18%; 40 of 22 840) were most likely the result of preanalytic or postanalytic errors. Interestingly, the variant allele fractions were almost uniformly lower than the engineered fraction (as measured by digital polymerase chain reaction). Extensive troubleshooting identified a multifactorial cause for the low variant allele fractions, a result of an interaction between the linearized nature of the plasmid and the Illumina TruSeq chemistry. Conclusions.— Laboratories demonstrated an overall accuracy of 99.2% (24 990 of 25 181) with 99.8% specificity and 93.5% sensitivity when examining 36 clinically relevant somatic single-nucleotide variants with a variant allele fraction of 10% or greater. The data also highlight an issue with artificial linearized plasmids as survey material for next-generation sequencing.

scholarly journals SNVMix: predicting single nucleotide variants from next-generation sequencing of tumors

2010 ◽  
Vol 26 (6) ◽  
pp. 730-736 ◽  
Author(s):  
Rodrigo Goya ◽  
Mark G.F. Sun ◽  
Ryan D. Morin ◽  
Gillian Leung ◽  
Gavin Ha ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Next Generation ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Generation Sequencing

scholarly journals SNVHMM: predicting single nucleotide variants from next generation sequencing

2013 ◽  
Vol 14 (1) ◽  
pp. 225 ◽  
Author(s):  
Jiawen Bian ◽  
Chenglin Liu ◽  
Hongyan Wang ◽  
Jing Xing ◽  
Priyanka Kachroo ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Next Generation ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Generation Sequencing

scholarly journals From next-generation sequencing alignments to accurate comparison and validation of single-nucleotide variants: the pibase software

2012 ◽  
Vol 41 (1) ◽  
pp. e16-e16 ◽  
Author(s):  
Michael Forster ◽  
Peter Forster ◽  
Abdou Elsharawy ◽  
Georg Hemmrich ◽  
Benjamin Kreck ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Next Generation ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Accurate Comparison ◽  
Generation Sequencing

scholarly journals Assembling and Validating Bioinformatic Pipelines for Next-Generation Sequencing Clinical Assays

2020 ◽  
Vol 144 (9) ◽  
pp. 1118-1130 ◽  
Author(s):  
Jeffrey A SoRelle ◽  
Megan Wachsmann ◽  
Brandi L. Cantarel
Keyword(s):  
Genetic Variation ◽  
Next Generation Sequencing ◽  
Proficiency Testing ◽  
Real World ◽  
Data Exchange ◽  
Genetic Alterations ◽  
Data Sets ◽  
Next Generation ◽  
Clinical Laboratories ◽  
Generation Sequencing

Context.— Clinical next-generation sequencing (NGS) is being rapidly adopted, but analysis and interpretation of large data sets prompt new challenges for a clinical laboratory setting. Clinical NGS results rely heavily on the bioinformatics pipeline for identifying genetic variation in complex samples. The choice of bioinformatics algorithms, genome assembly, and genetic annotation databases are important for determining genetic alterations associated with disease. The analysis methods are often tuned to the assay to maximize accuracy. Once a pipeline has been developed, it must be validated to determine accuracy and reproducibility for samples similar to real-world cases. In silico proficiency testing or institutional data exchange will ensure consistency among clinical laboratories. Objective.— To provide molecular pathologists a step-by-step guide to bioinformatics analysis and validation design in order to navigate the regulatory and validation standards of implementing a bioinformatic pipeline as a part of a new clinical NGS assay. Data Sources.— This guide uses published studies on genomic analysis, bioinformatics methods, and methods comparison studies to inform the reader on what resources, including open source software tools and databases, are available for genetic variant detection and interpretation. Conclusions.— This review covers 4 key concepts: (1) bioinformatic analysis design for detecting genetic variation, (2) the resources for assessing genetic effects, (3) analysis validation assessment experiments and data sets, including a diverse set of samples to mimic real-world challenges that assess accuracy and reproducibility, and (4) if concordance between clinical laboratories will be improved by proficiency testing designed to test bioinformatic pipelines.

scholarly journals Validation of OncoPanel: A Targeted Next-Generation Sequencing Assay for the Detection of Somatic Variants in Cancer

2017 ◽  
Vol 141 (6) ◽  
pp. 751-758 ◽  
Author(s):  
Elizabeth P. Garcia ◽  
Alissa Minkovsky ◽  
Yonghui Jia ◽  
Matthew D. Ducar ◽  
Priyanka Shivdasani ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Copy Number ◽  
Cancer Biology ◽  
Next Generation ◽  
Analytical Validation ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Insertions And Deletions ◽  
Targeted Next Generation Sequencing ◽  
Generation Sequencing

Context.— The analysis of somatic mutations across multiple genes in cancer specimens may be used to aid clinical decision making. The analytical validation of targeted next-generation sequencing panels is important to assess accuracy and limitations. Objective.— To report the development and validation of OncoPanel, a custom targeted next-generation sequencing assay for cancer. Design.— OncoPanel was designed for the detection of single-nucleotide variants, insertions and deletions, copy number alterations, and structural variants across 282 genes with evidence as drivers of cancer biology. We implemented a validation strategy using formalin-fixed, paraffin-embedded, fresh or frozen samples compared with results obtained by clinically validated orthogonal technologies. Results.— OncoPanel achieved 98% sensitivity and 100% specificity for the detection of single-nucleotide variants, and 84% sensitivity and 100% specificity for the detection of insertions and deletions compared with single-gene assays and mass spectrometry–based genotyping. Copy number detection achieved 86% sensitivity and 98% specificity compared with array comparative genomic hybridization. The sensitivity of structural variant detection was 74% compared with karyotype, fluorescence in situ hybridization, and polymerase chain reaction. Sensitivity was affected by inconsistency in the detection of FLT3 and NPM1 alterations and IGH rearrangements due to design limitations. Limit of detection studies demonstrated 98.4% concordance across triplicate runs for variants with allele fraction greater than 0.1 and at least 50× coverage. Conclusions.— The analytical validation of OncoPanel demonstrates the ability of targeted next-generation sequencing to detect multiple types of genetic alterations across a panel of genes implicated in cancer biology.

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